To understand: It happens when the export/import is being made by different charsets. Usually when the destination is a superset with “multibyting” and the source is a single-byte one. The reason is that as more as the charset is not specific, more bits are used to represent a charcter (c-ç, a-ã, o-õ-ô, for example), this way, the columns that uses as data length byte will be different sized between theese databases.

Of course, as more specific a charset configuration is, much better for performance constraints it’ll be (specially for sequencial reads), because the databases needs to work with less bytes in datasets/datablocks for the same tuples, in a simple way to explain. Otherside, this is a quite specific configuration. The performance issues are mostly related to more simple tunings (sql access plan, indexing, statistics or solution architecture) than this kind of details. But, it’s important to mention if you’re working in a database that is enough well tuned…

The follow image ilustrates in a simple way the difference of byting used to address more characters (a characteristic of supersets):

Ok, doke!
And the solution is…

Let’s summarize the problem first: The char (char, varchar) columns uses more bytes to represent the same characters. So the situations where, in the source, the column was used by the maximum lengh, it “explodes” the column lengh in the destination database with a multibyte encoding scheme.
For consideration, I’m not using datapump (expdp/impdp or impdb with networklink) just because it’s a legacy system with long columns. Datapump doesn’t support this “deprecated” type of data.
So, my solution, for this pontual problem occouring during a migration was to change the data lengh of the char columns from “byte” to “char”. This way, the used metric is the charchain rather than bytesize. Here is my “kludge” for you: